Mayo researchers develop algorithm to predict rheumatoid arthritis disease activity

Researchers within Mayo Clinic's Center for Individualized Medicine and Division of Rheumatology have developed a first-of-its-kind machine learning algorithm that can predict rheumatoid arthritis disease activity in a patient. "Having fast, reliable and scalable measures for predicting the clinical course of disease activity is an important unmet need for patients with rheumatoid arthritis,'' says Jaeyun Sung, Ph.D., a computational biologist within the Center for Individualized Medicine and co-senior author of the study. Dr. Sung develops computational analytical approaches to understand the intricate relationship between microbial organisms and human metabolic and immune health. The study, which was published in Arthritis Research & Therapy, lays the groundwork for monitoring rheumatoid arthritis disease progression and systemic inflammation using blood samples alone. The findings provide direction for the potential future development of clinical laboratory tests and digital diagnostics to further enable precision medicine for rheumatoid arthritis patients. "We turned to the blood because it could potentially provide a treasure-trove of novel biomarkers for assessing not only disease activity, but also clinical subgroups, risk factors and predictors of treatment response that complement current standard laboratory tests.